4.7 Article

Hydraulic conductivity imaging from 3-D transient hydraulic tomography at several pumping/observation densities

Journal

WATER RESOURCES RESEARCH
Volume 49, Issue 11, Pages 7311-7326

Publisher

AMER GEOPHYSICAL UNION
DOI: 10.1002/wrcr.20519

Keywords

hydraulic tomography; resolution; field study; hydrogeophysics; inversion

Funding

  1. NSF [0710949, 934680, 0934596]
  2. US Army RDE-COM ARL Army Research Office [W911NF-09-1-0534]
  3. Directorate For Geosciences
  4. Division Of Earth Sciences [0710949] Funding Source: National Science Foundation
  5. Division Of Mathematical Sciences
  6. Direct For Mathematical & Physical Scien [0934596] Funding Source: National Science Foundation

Ask authors/readers for more resources

3-D Hydraulic tomography (3-D HT) is a method for aquifer characterization whereby the 3-D spatial distribution of aquifer flow parameters (primarily hydraulic conductivity, K) is estimated by joint inversion of head change data from multiple partially penetrating pumping tests. While performance of 3-D HT has been studied extensively in numerical experiments, few field studies have demonstrated the real-world performance of 3-D HT. Here we report on a 3-D transient hydraulic tomography (3-D THT) field experiment at the Boise Hydrogeophysical Research Site which is different from prior approaches in that it represents a baseline analysis of 3-D THT performance using only a single arrangement of a central pumping well and five observation wells with nearly complete pumping and observation coverage at 1 m intervals. We jointly analyze all pumping tests using a geostatistical approach based on the quasi-linear estimator of Kitanidis (1995). We reanalyze the system after progressively removing pumping and/or observation intervals; significant progressive loss of information about heterogeneity is quantified as reduced variance of the K field overall, reduced correlation with slug test K estimates at wells, and reduced ability to accurately predict independent pumping tests. We verify that imaging accuracy is strongly improved by pumping and observational densities comparable to the aquifer heterogeneity geostatistical correlation lengths. Discrepancies between K profiles at wells, as obtained from HT and slug tests, are greatest at the tops and bottoms of wells where HT observation coverage was lacking.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.7
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

Article Water Resources

Deep learning technique for fast inference of large-scale riverine bathymetry

Hojat Ghorbanidehno, Jonghyun Lee, Matthew Farthing, Tyler Hesser, Eric F. Darve, Peter K. Kitanidis

Summary: Riverine bathymetry is important for shipping and flood management, and indirect measurements with sensor technology can be used to estimate river bed topography. Physics-based techniques are computationally expensive, while deep learning offers a data-driven approach with potential for efficient training using limited data. The proposed method combines DNN with PCA to image river bed topography using flow velocity observations, showing satisfactory performance in bathymetry estimation with low computational cost and small number of training samples.

ADVANCES IN WATER RESOURCES (2021)

Article Geography, Physical

Seasonality in cold coast bluff erosion processes

C. J. Roland, L. K. Zoet, J. E. Rawling, M. Cardiff

Summary: The study indicates that freeze-thaw environmental factors have a significant impact on the erosion of coastal bluffs at seasonal timescales, leading to increased pore pressures and frequent mass wasting events. Seasonal upslope erosion is primarily influenced by rising water levels and freeze-thaw processes, necessitating the inclusion of these transient conditions in landscape change models.

GEOMORPHOLOGY (2021)

Article Engineering, Environmental

Application of deep learning to large scale riverine flow velocity estimation

Mojtaba Forghani, Yizhou Qian, Jonghyun Lee, Matthew W. Farthing, Tyler Hesser, Peter K. Kitanidis, Eric F. Darve

Summary: This study proposes a two-stage process utilizing principal component geostatistical approach to estimate bathymetry probability density function and multiple machine learning algorithms to solve shallow water equations (SWEs) efficiently. The first stage predicts flow velocities without direct bathymetry measurement, while the second stage incorporates additional bathymetry information for improved accuracy and generalization. Fast solvers are capable of accurately predicting flow velocities with variable bathymetry and BCs at a significantly lower computational cost compared to traditional methods.

STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT (2021)

Article Environmental Sciences

Hydrogeophysical Characterization of Nonstationary DNAPL Source Zones by Integrating a Convolutional Variational Autoencoder and Ensemble Smoother

Xueyuan Kang, Amalia Kokkinaki, Peter K. Kitanidis, Xiaoqing Shi, Jonghyun Lee, Shaoxing Mo, Jichun Wu

Summary: Characterizing the architecture of dense nonaqueous phase liquid (DNAPL) source zones is crucial for designing efficient remediation strategies, but traditional drilling investigations provide limited information and affect the accuracy of geostatistical methods. By parameterizing the DNAPL saturation field using a physics-based approach, improved prior descriptions and better resolution can be achieved in characterizing the source zones. Additionally, incorporating hydrogeological and geophysical datasets in the inversion framework can further enhance the performance of the method.

WATER RESOURCES RESEARCH (2021)

Article Geosciences, Multidisciplinary

Aquifer Characterization and Uncertainty in Multi-Frequency Oscillatory Flow Tests: Approach and Insights

Jeremy R. Patterson, Michael Cardiff

Summary: Characterizing aquifer properties and their associated uncertainty is a challenge in hydrogeology. Using oscillatory flow interference testing can help characterize aquifer flow properties. Studies show that multi-frequency testing improves inversion performance and decreases parameter uncertainty.

GROUNDWATER (2022)

Article Mathematics, Interdisciplinary Applications

An information inequality for Bayesian analysis in imaging problems

Peter K. Kitanidis

Summary: This paper discusses the application of covariance and Fisher information matrix in inverse problems, as well as a reexamination within the Bayesian framework, proposing a lower bound for the covariance of the posterior probability density function.

GEM-INTERNATIONAL JOURNAL ON GEOMATHEMATICS (2021)

Article Geosciences, Multidisciplinary

Developing Data-Rich Video of Surface Water-Groundwater Interactions for Public Engagement

Catherine Christenson, David J. Hart, Michael Cardiff, Susan Richmond, Dante Fratta

Summary: This article presents a method for improving the communication of hydrologic data to the public by connecting data to video representations. The authors collected water-quality and geophysical data using multiple instruments mounted on a canoe and recorded video using GoPro cameras. The data was georeferenced and logged using an Arduino microcontroller. The results show that the low-cost sensors performed well and the data-rich video provided context for the measurements. This method enhances spatial understanding of hydrogeologic systems and facilitates communication and management of sensitive habitats.

GROUNDWATER (2022)

Article Geosciences, Multidisciplinary

Quantifying Annual Nitrogen Loss to Groundwater Via Edge-of-Field Monitoring: Method and Application

Michael Cardiff, Laura Schachter, Jake Krause, Madeline Gotkowitz, Brian Austin

Summary: Increased nitrate concentrations in groundwater and surface waters due to modern agriculture is a widespread and significant environmental issue. However, there is a lack of understanding regarding the specific contributions of individual agricultural fields and practices. In this study, a minimally invasive approach using edge-of-field monitoring and tracer application was developed to calculate annual nitrogen loss to groundwater. Results from a commercial field in Wisconsin showed that nitrogen losses were similar to previous studies, with more than 25% of applied nitrogen leaching to groundwater each year. This method provides a reliable estimation of nitrogen loss when using certain conditions, such as injecting the tracer directly at the water table and analyzing nitrate concentrations in the laboratory.

GROUNDWATER (2023)

Article Environmental Sciences

Hierarchical Bayesian Inversion of Global Variables and Large-Scale Spatial Fields

Lijing Wang, Peter K. Kitanidis, Jef Caers

Summary: Bayesian inversion is commonly used to quantify uncertainty of hydrological variables. This paper proposes a hierarchical Bayesian framework to quantify uncertainty of both global and spatial variables. The authors present a machine learning-based inversion method and a local dimension reduction method to efficiently estimate posterior probabilities and update spatial fields. Using three case studies, they demonstrate the importance of quantifying uncertainty of global variables for predictions and the acceleration effect of the local PCA approach.

WATER RESOURCES RESEARCH (2022)

Article Water Resources

Variational encoder geostatistical analysis (VEGAS) with an application to large scale riverine bathymetry

Mojtaba Forghani, Yizhou Qian, Jonghyun Lee, Matthew Farthing, Tyler Hesser, Peter K. Kitanidis, Eric F. Darve

Summary: This article presents a reduced-order model (ROM) based approach that utilizes a variational autoencoder (VAE) to compress bathymetry and flow velocity information, allowing for fast solving of bathymetry inverse problems. By constructing ROMs on a nonlinear manifold and employing a Hierarchical Bayesian setting, variational inference and efficient uncertainty quantification can be achieved using a small number of ROM runs.

ADVANCES IN WATER RESOURCES (2022)

Letter Geosciences, Multidisciplinary

Comment on Aquifer Characterization Using Fiber Bragg Grating Multi-Level Monitoring System

Carsten Leven, Warren Barrash

GROUNDWATER (2022)

Article Environmental Sciences

Integration of Deep Learning-Based Inversion and Upscaled Mass-Transfer Model for DNAPL Mass-Discharge Estimation and Uncertainty Assessment

Xueyuan Kang, Amalia Kokkinaki, Xiaoqing Shi, Hongkyu Yoon, Jonghyun Lee, Peter K. Kitanidis, Jichun Wu

Summary: This study presents a framework that combines a deep-learning-based inversion method with a process-based upscaled model to estimate source zone architecture (SZA) metrics and mass discharge from sparse data. By improving the estimation method, the upscaled model accurately reproduces the concentrations and uncertainties of multistage effluents, providing valuable input for decision making in remediation applications.

WATER RESOURCES RESEARCH (2022)

Article Environmental Sciences

Statistical Analysis of Aquifer Hydraulic Properties by a Continuous Pumping Tomography Test: Application to the Boise Hydrogeophysical Research Site

Kan Bun Cheng, Gedeon Dagan, Warren Barrash, Michael Cardiff, Avinoam Rabinovich

Summary: Characterizing aquifer heterogeneity is crucial for accurate flow and transport modeling. This study presents a new approach for statistically analyzing hydraulic properties in continuous pumping tomography tests of phreatic aquifers. The method involves determining equivalent hydraulic conductivity, specific storage, and specific yield at multiple locations and calculating statistical moments assuming random space variables. The results show that the spatial averages of the equivalent properties decrease with distance from the pumping well and stabilize at larger distances, consistent with existing theory.

WATER RESOURCES RESEARCH (2022)

Article Geosciences, Multidisciplinary

Do Simple Analytical Models Capture Complex Fractured Bedrock Hydraulics? Oscillatory Flow Tests Suggest Not

Jeremy R. R. Patterson, Michael Cardiff

Summary: Fractured sedimentary bedrock aquifers are complex flow systems with fast fractures and slow porous media-dominated flow paths. Previous studies have used oscillatory flow testing to characterize single bedrock fractures but relied on an idealized analytical model. This study extends the testing to fractured sedimentary bedrock and suggests that other hydraulic processes are needed to accurately represent pressure propagation.

GROUNDWATER (2023)

Article Environmental Sciences

Aquifer conditions, not irradiance determine the potential of photovoltaic energy for groundwater pumping across Africa

Simon Meunier, Peter K. Kitanidis, Amaury Cordier, Alan M. MacDonald

Summary: This study develops a numerical model to simulate the abstraction capacities of photovoltaic water pumping systems across Africa using openly available data. The model includes realistic geological constraints on pumping depth and sub-hourly irradiance time series. The simulation results show that for much of Africa, groundwater pumping using photovoltaic energy is limited by aquifer conditions rather than irradiance. These findings can help identify regions with high potential for photovoltaic pumping and guide large-scale investments.

COMMUNICATIONS EARTH & ENVIRONMENT (2023)

No Data Available